Impacts of Integrating Computer Simulation into Genetics on Seventh Graders’ Cognitive Achievement, Learning Motivation, and Flow Experience

碩士 === 國立臺灣師範大學 === 科學教育研究所在職進修碩士班 === 102 === To the 7th graders, the most difficult in Life and Technology Learning Area are the units related to genetics. Since genetics is microscopic and abstract, students are very likely to form alternative conceptions of it if the units are taught with inappr...

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Bibliographic Details
Main Authors: Chen, Chu-heng, 陳俊亨
Other Authors: 張文華
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/03774082403240491401
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Summary:碩士 === 國立臺灣師範大學 === 科學教育研究所在職進修碩士班 === 102 === To the 7th graders, the most difficult in Life and Technology Learning Area are the units related to genetics. Since genetics is microscopic and abstract, students are very likely to form alternative conceptions of it if the units are taught with inappropriate methods. By integrating the software Pedagogica into learning genetics, the purpose of this research was to find out the influences of the practices of simulation software on the learning motivation and flow experience of students with different levels of achievements. This research was practiced by contrasting the pre-test and post-test scores of a group. The subjects consist of eighty-one students in three different classes. The process was completed with two students operating one computer. During the process, the teacher used the simulation software to introduce concepts related to genetics, while the students completed the questions in the handouts by practicing the software. The tools utilized in this research included tests of achievement in genetics, SMTSL, flow experience scale, and instruments of flow dimensions. The results of this research are as follows. 1.High-achieving groups scored higher in tests of achievement in genetics than middle-achieving and low-achieving ones (p<.05). Middle-achieving groups scored higher in tests of achievement in genetics than low-achieving ones (p<.05). 2.High-achieving groups scored higher in SE than middle-achieving ones(p<.05); in ALS , high-achieving groups scored higher than low-achieving ones(p<.05). 3.As a whole, the post-test score and the progress between the pre-test and post-test scores in tests of achievement in genetics had significantly a positive correlation with their flow experience. 4.Multiple regression analysis indicated that scores in flow experience can predict the learning motivation of students with different levels of achievements.